Review Article Open Access

A SURVEY ON PERIODICITY DETECTION IN TIME SERIES DATABASE

Abstract

Research on periodic pattern mining has attained a great focus on nowadays. It is the problem that regards temporal regularity. There are many emerging applications in periodic pattern mining, including weather predictions, computer networks and biological data. The discovery of patterns with periodicity is of great importance and has been rapidly developed in recent years. The problem of discovering periods for time series databases, referred as periodicity detection. These types of periodicities are available such as symbol periodicity, sequence periodicity and segment periodicity and they are identified even in the presence of noise in the time series database. Using pruning strategy some of these patterns are identified and extracted from the given time series database. There are different techniques already exists for periodic pattern mining. Those existing techniques have their own merits and demerits. This paper presents a survey on some of the existing periodic pattern mining techniques.

B.Sujatha, Dr.S.Chenthur Pandian

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